Embodiments of the invention relate generally to measurement instruments, and more particularly, to a system and a method for measurement or imaging.
Soft field tomography (SFT) is a technique that measures or images the internal structure of an object, such as a region of a human body by computing a distribution of one or more properties of the internal structure. SFT includes, but is not limited to, Electrical Impedance Tomography (EIT), Electrical Impedance Spectroscopy (EIS), Diffuse Optical Tomography (DOT), Microwave Tomography, Elastography, and Magnetic Induction Tomography (MIT). In the example of reconstructing properties of the human chest using EIT, electrical properties are different for air and body tissues. Moreover, the electrical properties of the body tissues also vary with time. Accordingly, a time-varying map of the electrical properties within the body region can be generated.
A typical SFT system for measuring or imaging distributed properties of an object comprises a plurality of sensing elements arranged on a peripheral surface of the object to be imaged. Excitations are applied to all or a subset of the sensing elements, and a measurement device measures the response of all or a subset of the sensing elements. The applied excitations and measured responses are processed to create a two-dimensional or three-dimensional property distribution of the object, which may be processed into one or more images. In the example of EIT, the sensing elements are electrodes that conduct electrical current. The excitations applied to the electrodes can be electrical current, and the measured response can be voltages. The property distribution of the internal structure to be determined can be a distribution of electrical impedance, electrical admittivity, electrical permittivity, or electrical conductivity.
One method for computation of the property distribution of the internal structure uses finite element modeling (FEM), which discretizes the space inside the object into finite elements. The properties on these elements are solved with an inverse solver, for example, based on a forward mapping of applied currents or voltages on the conductivity distribution to measured voltages or currents on the electrodes. A two-dimensional or three-dimensional image of the internal structure of the object may be obtained based on the computed property distribution.
The resolution of the image obtained using typical SFT systems is restricted by the number of independent measurements available, or in other words, by the number of sensing elements employed. Generally, the more solvable finite elements there are in the FEM analysis, the better the resolution of the obtained image will be. For a given number of sensing elements, the number of solvable variables is limited. One conventional method for improving the resolution of the measurement is to increase the number of sensing elements applied to the object. However, for a fixed excitation energy and system precision, the signal-to-noise ratio drops with the increase of the number of the sensing elements. Further, a large number of sensing elements make the system bulky and expensive.
There is a need in the art to provide a different SFT system and method with improved resolution at regions of interest without adding to the number of sensing elements applied to the object to be measured.